Machine Learning Engineer, Stripe

• You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment
• 2+ years of industry experience building and shipping ML systems in production
• Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark
• Knowledge of various ML algorithms and model architectures
• Hands-on experience in designing, training, and evaluating machine learning models
• Hands-on experience in productionizing and deploying models at scale
• Hands-on experience in orchestrating complicated data pipelines and efficiently leveraging large-scale datasets
• Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets
• Proficiency in creatively applying modern machine learning techniques and Generative AI models to solve complex business problems

Desirable

• As a machine learning engineer in Supportability, you will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production
• You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products
• You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community
• Design state-of-the-art ML models and large scale ML systems for detection and decisioning for Stripe products based on ML principles, domain knowledge, and engineering constraints
• Drive the expansion of Stripe's largest LLM-based system, scaling its usage and integrating new capabilities through agentic approaches or supervised learning
• Rapidly prototype new ML-based approaches to achieve key business goals
• Develop pipelines and automated processes to train and evaluate models in offline and online environments
• Integrate ML models into production systems and ensure their scalability and reliability
• Collaborate with product and strategy partners to propose, prioritize, and implement new product features
• Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions
• Explore cutting-edge ML techniques and evaluate their potential to solve business problems
• Identify high-impact opportunities, and drive the long-term ML roadmap through well-scoped high-leverage initiatives
• We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions
• You have experience developing efficient feature pipelines, building and evaluating advanced ML models, and deploying them to production